Country 'choices' or deforestation paths: a method for global change analysis of human-forest interactions

Data used in quantitative studies of global tropical deforestation are typically of poor quality. These studies use either cross-sectional or panel data to measure the contribution of social and land use factors to forest decline world wide. However, there are pitfalls in the use of either type of data. Panel data studies treat each year's observation as a distinct, reliable, data point, when a careful examination of the data reveals this assumption to be implausible. In contrast, cross-sectional studies discard most of the time series information in the data, calculating a single average deforestation rate for each country. In this paper, we argue for a middle road between these two approaches: one that does not treat the time series information as completely reliable but does not disregard it altogether. Using a well-known global forest data set (FAO'sProduction Series Yearbooks ), we argue that the most the data can reliably tell us is whether a country's deforestation rate falls into one of four categories or country 'path choices'. We then use the data categorised in this way in a small empirical investigation of the socio-economic causes of deforestation. This multinomial logit framework allows for the determination of the influence of independent variables on the probability that a country will follow one deforestation path vs. another. Results from the logit analysis of key social and land use indicators chosen for their importance in the literature in driving deforestation suggest that the effect of these variables will differ for countries depending on the particular set of deforestation trajectories in question.